Salesforce AI Specialist Salesforce Certified AI Specialist Exam Practice Test

Answer : C

Context of the Question

Universal Containers (UC) has generative AI--enabled fields that users can access in the desktop experience.

The AI Specialist needs these same fields to be visible and usable in the Salesforce Mobile App.

Why Dynamic Forms on Mobile?

Dynamic Forms allow you to configure record pages so that fields and sections can appear or be hidden based on certain criteria.

When you enable ''Dynamic Forms for Mobile,'' any generative AI--enabled fields placed on the dynamic layout become accessible in the Salesforce mobile experience.

There is no standard Setup option labeled ''Enable Mobile Generative AI'' or ''Enable Mobile Prompt Responses'' as a universal toggle; the existing official approach is to ensure dynamic forms (and the relevant fields) are supported on mobile.

Conclusion

Ensuring that these AI-driven fields are visible on mobile is accomplished by turning on Dynamic Forms on Mobile and adding those fields to the dynamic layout. Therefore, Option C is correct.

Salesforce AI Specialist Reference & Documents

Salesforce Documentation: Dynamic Forms Overview Explains how to enable Dynamic Forms for both desktop and mobile UIs, allowing newly added fields (including generative AI--enabled ones) to display in the Salesforce Mobile App.

Salesforce AI Specialist Study Guide Reiterates that to expose generative AI fields or components in mobile, you must configure dynamic forms and ensure compatibility on mobile layouts.

Answer : B

Context of the Question

Universal Container (UC) has used prompt templates to update summary fields on record pages.

Now, the admin wants to incorporate similar generative AI functionality within a Flow for automation purposes.

How to Call a Prompt Template Within a Flow

Flow Action: Salesforce provides a standard way to invoke generative AI templates or prompts within a Flow step. From the Flow Builder, you can add an ''Action'' that references the prompt template you created in Prompt Builder.

Other Options:

Invocable Apex: Possible fallback if there's no out-of-the-box Flow Action available. However, Salesforce is releasing native Flow integration for AI prompts, making custom Apex less necessary.

Einstein for Flow: A broad label for Salesforce's generative AI features within Flow. Under the hood, you typically use a ''Flow Action'' that points to your prompt.

Conclusion

The easiest out-of-the-box solution is to use a Flow Action referencing the prompt template. Hence, Option B is correct.

Salesforce AI Specialist Reference & Documents

Salesforce Trailhead: Use Prompt Templates in Flow Demonstrates how to add an Action in Flow that calls a prompt template.

Salesforce Documentation: Einstein GPT for Flow Explains standard flow actions to invoke and handle generative AI responses.

Answer : C

Context of the Question

Universal Containers (UC) wants to build a Flex prompt template that uses data returned by a Flow.

''Flex Prompt Templates'' allow admins and AI Specialists to incorporate external or dynamic data into generative AI prompts.

Why ''Add Flow Instructions'' Is Needed

Passing Flow Data into Prompt Templates: When configuring the prompt, you must specify how data from the running Flow is passed into the Flex template. The designated element for that is typically ''Flow Instructions,'' which map the Flow outputs to the prompt.

Other Options:

Add Flex Instructions: Typically controls how the AI responds or structures the output, not how to bring Flow data into the template.

Add Prompt Instructions: Usually for static or manual instructions that shape the AI's response, rather than referencing dynamic data from the Flow.

Outcome

''Add Flow Instructions'' ensures the prompt can dynamically use the data that the Flow returns---making Option C correct.

Salesforce AI Specialist Reference & Documents

Salesforce Help & Training: Using Prompt Templates with Flow Explains how to pass Flow variables into a prompt template via a specialized step (e.g., ''Flow Instructions'').

Salesforce AI Specialist Study Guide Outlines how to configure generative AI prompts that reference real-time Flow data.

Answer : C

Context of the Question

Universal Containers (UC) has a strict change management process that requires all possible configuration be completed in a sandbox and deployed to Production.

Einstein Generative AI is already enabled in Production, and the ''Einstein Work Summaries'' permission set is already available in Production.

The AI Specialist needs to configure Work Summaries for Enhanced Messaging in the sandbox.

What Can Actually Be Deployed from Sandbox to Production?

Custom Fields: Metadata that is easily created in sandbox and then deployed.

Quick Actions: Also metadata-based and can be deployed from sandbox to production.

Layout Components: Page layout changes (such as adding the Wrap Up component) can be added to a change set or deployment package.

Why Option C is Correct

No Need to Turn on Einstein in Sandbox for Deployment: Einstein Generative AI is already enabled in Production; turning it on in the sandbox is typically a manual step if you want to test, but that step itself is not ''deployable'' in the sense of metadata.

Permission Set Assignments (as in Option A) are not deployable metadata. You can deploy the Permission Set itself but not the specific user assignments. Since the question specifically asks ''Which other configuration steps should be taken in the sandbox that can be deployed to the production org?'', user assignment is not one of them.

Why Not Option A or B?

Option A: Mentions creating permission set assignments for agents. This cannot be directly deployed from sandbox to Production, as permission set assignments are user-specific and considered ''data,'' not metadata.

Option B: Mentions ''Turn on Einstein.'' But Einstein Generative AI is already enabled in Production. Additionally, ''Turning on Einstein'' is typically an org-level setting, not a deployable metadata item.

Conclusion The main deployable items you can reliably create and test in a sandbox, and then migrate to Production, are:

Custom Fields (Issue, Resolution, Summary).

A Quick Action that updates those fields.

Page Layout Change to include the Wrap Up component.

Therefore, Option C is correct and focuses on actions that are truly deployable as metadata from a sandbox to Production.

Salesforce AI Specialist Reference & Documents

Salesforce Trailhead: Work Summaries with Einstein GPT Provides an overview of how to configure Work Summaries, including the need for custom fields, quick actions, and UI components.

Salesforce Documentation: Deploying Metadata Between Orgs Explains what can and cannot be deployed via change sets (e.g., custom fields, page layouts, quick actions vs. user permission set assignments).

Salesforce AI Specialist Study Guide Outlines which Einstein Generative AI and Work Summaries configurations are deployable as metadata.

Answer : C

Context of the Question Universal Containers (UC) uses Agentforce, a specialized AI-driven assistant for Salesforce. A user reports that an Agent is unable to delete recent activities.

Why Agentforce Cannot Delete Records

Agentforce's Standard Actions: Agentforce typically has predefined or ''standard'' actions like Create, Update, or Summarize records. However, a standard Delete Record action is not part of the default set of Agentforce actions.

Implication: If Agentforce has no built-in delete functionality, it cannot remove activities---even if the user has permission to delete them in the Salesforce UI.

Why Other Options Are Incorrect

Option A -- Permission to Delete the User's Records: Standard Salesforce user permissions do not automatically extend to Agentforce's capabilities. Even if the user can delete records, that doesn't grant Agentforce a new action.

Option B -- Agentforce Delete Record Action Permission: There is no separate ''Delete Record Action permission'' for Agentforce to be toggled. The relevant issue is that the standard Delete Record action does not exist within Agentforce out of the box.

Conclusion The core reason for the issue is that Agentforce does not support a standard Delete Record action (Choice C).

Salesforce AI Specialist Reference & Documents

Salesforce Official Documentation -- Agentforce (Note: Agentforce may be a pilot or specialized feature; check pilot release notes or official docs for standard actions.)

Salesforce AI Specialist Study Guide Covers the limitations of certain AI-enabled features regarding record operations.

Answer : A

Context of the Question Universal Containers (UC) wants to include details from a related list on the Account object in a prompt template. This is typically done via Prompt Builder in Salesforce's generative AI setup.

Prompt Builder Behavior

Selecting a Related List: Within Prompt Builder, you can navigate to the object (Account) and choose which related list (e.g., Contacts, Opportunities) you want to reference.

Field Picker: Once a related list is chosen, Prompt Builder provides a field picker interface, allowing you to select specific fields from that related list. These fields then become available for merge fields or dynamic insertion within your prompt.

Why Option A is Correct

Direct Alignment with the Standard Process: The recommended approach in Salesforce's documentation is to select a related list and then use the field picker to add the necessary fields into your AI prompt. This ensures the prompt has exactly the data you need from that related list.

Why Not Option B (JSON Formatting)

No Mandatory JSON Requirement: Although you can structure data as JSON if you desire advanced formatting, Prompt Builder does not require you to manually assign the fields from the related list in JSON. The platform automatically handles how the data is passed along in the background.

Why Not Option C (Default Page Layout)

Independent of Page Layout: Prompt Builder does not rely strictly on the default page layout for fields. You can configure the fields you want from the related list, independent of how the user's page layout is set up in the UI.

Conclusion Since the official Salesforce approach involves selecting a related list and then using the field picker to insert merge fields, Option A is the correct and verified answer.

Salesforce AI Specialist Reference & Documents

Salesforce Official Documentation: Prompt Builder Basics Explains how to reference objects and related lists when building AI prompts.

Salesforce Trailhead: Get Started with Prompt Builder Provides hands-on exercises demonstrating how to pick fields from related objects or lists.

Salesforce AI Specialist Study Guide Outlines best practices for referencing related records and fields in generative AI prompts.

Answer : A

Context of the Questio n: Universal Containers (UC) wants to harness generative AI to boost sales productivity. They are wary of public AI virtual assistants (like generic chatbots) that lack sufficient UC-specific data to generate useful business responses.

Why Fine-Tune an Einstein AI Model with CRM Data?

Company-Specific Relevance: By fine-tuning Einstein AI with UC's CRM data (accounts, opportunities, products, and historical interactions), the model learns the enterprise-specific context. This ensures that the generative outputs are accurate and tailored to UC's sales scenarios.

Security and Compliance: Using Salesforce Einstein within the Salesforce ecosystem keeps data under UC's control, aligning with trust, security, and compliance requirements.

Better Predictions: Einstein AI can produce more relevant insights (e.g., recommended next steps, content suggestions, or AI-generated email responses) when it has been trained on real, high-quality internal data.

Why Not Build an AI Model with Einstein Discovery (Option B)?

Einstein Discovery Use Case: Einstein Discovery is best suited for predictive and prescriptive analytics (e.g., analyzing large data sets for patterns, scoring leads, or predicting churn). While it provides advanced analytics, it is not primarily designed for generative text-based interactions for end-user consumption in a conversational format.

Why Not Enable Agentforce (Option C)?

Agentforce Overview: ''Agentforce'' (sometimes referencing a pilot or non-mainstream name) typically focuses on interactive help or workforce collaboration. It does not inherently solve the problem of large-scale generative AI using internal CRM data. Moreover, you still need a robust generative engine fine-tuned on company data.

Outcome: Fine-tuning the Einstein AI model with UC's CRM data (Answer A) is the most direct, Salesforce-native solution to provide generative AI responses that are aligned with UC's context, driving productivity gains and ensuring data privacy.

Salesforce AI Specialist References & Documents

Salesforce Official: Einstein GPT Overview

Discusses how Einstein GPT can be fine-tuned with specific CRM data to deliver contextually relevant, generative AI responses.

Salesforce Trailhead: Get Started with Salesforce Einstein

Explains the fundamentals of AI within the Salesforce platform, including training and optimizing Einstein models.

Salesforce Documentation: Einstein Discovery

Details how Einstein Discovery is primarily used for advanced analytics and predictions, not direct generative text solutions.

Salesforce AI Specialist Study Guide

Provides the official outline of Einstein AI capabilities, referencing how to configure and fine-tune models for specialized enterprise use cases.